In this article, we have developed an encryption technique to encrypt any kind of digital information. The main work is to construct the component of the block ciphers namely the substitution boxes (S-boxes) over an algebraic structure of finite chain ring; and then use these S-boxes in image encryption applications. The present formation is based on the finite commutative chain ring R9 = ℤ2 + uℤ2 + … + uk − 1ℤ2

In the field of agriculture science, automatic visual inspection improves the commercial, quality and fertility of the country. It is very challenging to sort the fruit based on quality because of varieties of fruits available in the market. Human grades the fruit but it is inconsistent, stagnant, and expensive and influenced by the surrounding. Thus an effective system for grading of fruit is desired

Face recognition is a challenging task as it has to deal with several issues such as illumination orientation and variability among the different faces. Previous works have shown that 3D face is a robust biometric trait and is less sensitive to light and pose variations. Also due to availability of inexpensive sensors and new 3D data acquisition techniques it has become easy to capture 3D data. A 3D

With the explosive growth of mobile video consumption over the Internet, delivering video at high quality while controlling the energy consumption of embedded decoding devices is becoming a primary concern. In this context, this paper demonstrates that tailored energy savings strategies, coupled with a video quality assessment protocol, have the potential to reduce the energy consumption of video decoding

In this paper, we propose an efficient cascaded model for sign language recognition taking benefit from spatio-temporal hand-based information using deep learning approaches, especially Single Shot Detector (SSD), Convolutional Neural Network (CNN), and Long Short Term Memory (LSTM), from videos. Our simple yet efficient and accurate model includes two main parts: hand detection and sign recognition

Virtual Learning Environments (VLEs) are spaces designed to educate student groups remotely via online platforms. Although traditional VLEs have shown promise in educating students, they offer limited immersion that overall diminishes learning effectiveness. In this paper, we describe vSocial, a cloud-based virtual reality learning environment (VRLE) system that can be deployed over high-speed networks

Palm print scanning is a widespread method for biometric identity detection which has some advantages over other methods including its simplicity and relatively lower cost. In this study, a novel methods for biometric verification and identification by contactless palm scanning technique is proposed. In the study, Ripplet-I Transform (R-IT) which is a generalized form of Curvelet Transform (CuT), have

Promotional 360∘ videos are now widely used to promote touristic sites, giving consumers a more immersive glimpse of what they can expect from those places. However, these 360∘ videos often comprise so much information that it overloads the users, not allowing them to benefit from such a rich multimedia experience. To overcome this issue, we propose and evaluate a novel method that allows the experience

Digital images are among the most communicated multimedia data types. Many of these images include private data that require a high level of security. The traditional image security schemes rely on cryptographic solutions to ensure the confidentiality or the authentication of image contents, and to ensure that the encryption key is not compromised. However, the continuous evolution of the attackers’

Recent years have witnessed the proliferation of online fashion blogs and communities, where a large amount of fashion model images with chic clothes in various scenarios are publicly available. To facilitate users to find the corresponding clothes, we focus on studying how to generate pure wellshaped clothing items with the best view from the complex model images. Towards this end, inspired by painting

We propose a framework to combine various quality metrics using a full reference approach for High Dynamic Range (HDR) Image quality assessment (IQA). We combine scores from metrics exclusively designed for different applications such as HDR, Standard Dynamic Range (SDR) and color difference measures, in a non-linear manner using machine learning (ML) approaches with weights determined during an offline

With the advent of cloud and social networking sites, information security has become a major issue. Images are the most searched, uploaded, and shared data in multimedia. However, existing encryption algorithms such as DES and AES may not be suitable for image encryption because digital images have large data size, high redundancy, and strong correlation between pixels. To overcome these problems

Person re-identification plays important roles in many practical applications. Due to various human poses, complex backgrounds and similarity of person clothes, person re-identification is still a challenging task. In this paper, we mainly focus on the robust and discriminative appearance feature representation and proposed a novel multi-appearance method for person re-identification. First, we proposed

Image is a typical example of visual data, and its quality inevitably affects its application. Hence, measuring image quality accurately is a beneficial task. In practical application, there are different image types e.g. natural image and screen content image (SCIs). And the distortion types contained in images are various. Most image quality assessment (IQA) methods concentrate on a single image

In recent years, convolutional neural networks (CNN) have been extensively used for generic object detection due to their powerful feature extraction capabilities. This has hence motivated researchers to adopt this technology in the field of remote sensing. However, remote sensing images can contain large amounts of noise, have complex backgrounds, include small dense objects as well as being susceptible

To prevent man-in-the-middle attack, Diffie-Hellman first proposed the concept of the session key exchange protocol, in which the author remove the long term keying material at the end of the session. In our scheme, we apply the session key concept of Diffie-Hellman for cloud computing in the presence of the Trusted Third Party (TTP). Our proposed scheme provides SEVEN security properties by using

Sentiment analysis, an application of machine learning in business is the process of identifying and cataloging comments, reviews, tweets, feedback, and even random rants according to the tone or sentiments conveyed by it. The data is analysed using machine learning approach of Long Short Term Memory (LSTM) rating the sentiments on a scale ranging from −100 to 100. A new proposed activation function

One of the most recent trends in the evaluation of immersive virtual environments is the incorporation of user metrics. In this article, we conduct a user study on a 360° hypervideo, using a dashboard based on detailed metrics obtained from users’ interactions with 360° hypervideos. It is essential to evaluate the quality of experience to monitor service quality from the perspectives of consumers.

Human identification plays a significant role in ensuring social security. However, face-based and appearance-based retrieval methods are not effective in monitoring due to the long distance and low camera resolution. Compared with other biological characteristics, the gait of humans has a strong discriminating ability even at long distance and low resolution. In this paper, the deep mutual learning

An imperceptible digital watermarking algorithm based on 4-level discrete wavelet transform, discrete cosine transform and singular value decomposition is designed. In this method, the 4-level diagonal sub-band image is obtained by performing the 4-level two-dimensional wavelet transform on the original image, and then a coefficient matrix is produced by applying the discrete cosine transform on the

Numerous seismic datasets are routinely acquired, stored and transferred via different systems and networks. Significant reduction of data sizes with encryption would significantly reduce storage media and transmission costs and security. This study presents a novel approach for compressing and encrypting numerical data in descriptive bitmap images. The method depends on the Steim method for bit-packing

This paper introduces a steganography technique using the concept of virtual bit-plane. Purposely another number system has been used in this technique instead of binary to hide the target data. After that embedding of target data is done on different bit-planes. Here for conversion, Lucas Number system is used. The Lucas sequence is almost similar to Fibonacci, instead 1 and 2 it starts with 2 and

Human action recognition (HAR)in videos is a challenging task in computer vision. Conventional methods are prone to explore the spatiotemporal or optical representations for video actions. However, optical representation might be inefficient in some real-life situations, such as object occlusion and dim light. To address this issue, this paper presents a novel approach for human action recognition

Recently, with the rapid development of digital technologies and its wide application, 3D model retrieval is becoming more and more important in graphic communities. In this task, how to effectively represent the 3D model and how to robustly measure similarity between pair-wise models are two crucial problems. In previous work, most papers dedicated to researching how to effectively using the visualize

Improved Pixel-Value-Ordering (I-PVO) based reversible data hiding scheme provides high-fidelity watermarked images with high data embedding capacity. In this paper, a new reversible data hiding scheme based on the I-PVO method is proposed to increase the data embedding capacity. The proposed scheme first divides the cover image into non-overlapping blocks of size 2 × 2 pixels uniformly, and then increases

Image Processing is one of the vibrant research areas nowadays and particularly face recognition is given much importance in all the sectors. Accordingly this research paper proposes a hybrid Face Recognition System to find facial changes due to the aging factor in a robust manner. The highly qualified sharp features are extracted using the algorithms SURF(Speed Up Robust Features), HOG(Histogram of

Nowadays, robots are indispensable in industry, especially logistics industry, to replace human employees performing heavy lifting tasks. Introducing robots prevents musculoskeletal disorders that are common in ageing workforce. We designed and implemented a dual arm robot to grasp cardboard boxes of different dimensions using a hydrid force/position control. In a first step, the position of the cardboard

Text classification has been a fundamental problem in the realm of Natural Language Processing (NLP), and a variety of approaches have been proposed with the development of deep learning. Despite recent progress, most existing approaches deal with the problem of multi-class text classification in a flat way, assuming that text labels are semantically independent. This assumption doesn’t always hold

In India, nearly 12 million visually impaired people had difficulty in identifying the currency notes. There is a need to develop an application that can recognize the currency note and provide a vocal message. In this paper, a novel lightweight Convolutional Neural Network (CNN) model is developed for efficient web and mobile applications to recognize the Indian currency notes. A new dataset for Indian

In recent years, the aging of the population has attracted considerable attention in the scientific community. An important fact is an increasing number of senior people will suffer from cognitive decline and there is almost no existing way to detect it early without the intervention of a clinician. Indeed, the sooner the cognitive decline is detected, the professional can elaborate a more adequate

Person re-identification (re-id) is the task of recognizing images of the same pedestrian captured by different cameras with non-overlapping views. Person re-id is a challenging task due to the existence of large view variations, such as spatial misalignment, background clutter and human poses change. In this paper, we handle these challenges from the following two aspects: utilizing attention mechanism

Cancer in Liver is the one among all other types of cancer which causes death of carcinogenic victim people throughout the world. GLOBOCAN12 was an initiative for simultaneously generating the expected dominance and mortality incidence that raised out of the cancer over the whole globe. It reported that about 782,000 new cases in the population were reported to have liver cancer, in which around 745

Nowadays, with the development of public network usage, medical information is transmitted throughout the hospitals. A watermarking system can help for the confidentiality of medical information distributed over the internet. In medical images, regions-of-interest (ROI) contain diagnostic information. The watermark should be embedded only into non-regions-of-interest (NROI) regions to keep diagnostically

Biological threats are becoming a serious security issue for many countries across the world. Effective biosurveillance systems can primarily support appropriate responses to biological threats and consequently save human lives. Nevertheless, biosurveillance systems are costly to implement and hard to operate. Furthermore, they rely on static infrastructures that might not cope with the evolving dynamics

As an important biological feature of the human, the skull plays an active role in assisting criminal investigation, victim identification, etc. This paper proposes a method based on Sparse Principal Component Analysis (SPCA) for comparison of skull similarity. Compared with Principal Component Analysis (PCA), SPCA can not only effectively reduce the data dimension,but also produce sparse principal

The speedy development of digital imaging and computer vision has extended the potential of using these technologies in ophthalmology. Image processing systems are increasingly prominent in medical diagnostic systems and especially to modern ophthalmology. The retinal images give information about the health of the visual system. Retinal diseases, such as glaucoma, diabetic retinopathy, age-related

This paper focuses on dealing with the tracking challenges such as target occlusion and deformation. It proposes a new tracking method via extracting and evaluating multi-features for both target region and its adjacent surroundings. The multi-features separately describe the key factors to detect target including the color feature, the shape and contour feature, and the distributions of structure

Denoising of natural images is a basic problem in image processing. The present paper proposes a new algorithm for image denoising based on the maximum a-posteriori (MAP) estimator in undecimated dual-tree complex wavelet transform. The undecimated dual-tree complex wavelet transform (UDT-CWT), along with the directional selectivity of the dual-tree complex wavelet transform (DT-CWT), offers exact

Hearing loss is the principle cause behind hearing impairment and deafness around the world. It is a significant health problem affecting our world today and it is growing exponentially among young and adults due to aging, hearing impairment, listening to music and noise exposure. Treatment options for hearing loss are very limited and it can only be controlled by taking precautions in the early stages

The extraction of blood vessels helps in the diagnosis of diseases and to develop advances of medicine. Retinal blood vessel extraction plays a crucial role in early detection and treatment of retinal diseases. This paper provides an automatic segmentation of blood vessels in retinal images. First, the fundus images go through preprocessing steps of image acquisition, grey scale conversion, bias correction

Sentiment lexicon is used to judge the sentiments of words and plays a significant role in sentiment analysis. Existing sentiment lexicons ignore the sentimental ambiguity of words in different contexts and only assign sentiment positive or negative polarity for words. In this paper, we propose an automatic method for the construction of the domain-specific sentiment lexicon (SDS-lex) to avoid sentimental

The Secret Sharing Scheme plays a vital role in cryptography which allows to transmit the secret digital information (image, video, audio, handwriting, etc.,) over a communication channel. This cryptographic technique involves encrypting the secret images into noisy shares and transmitted. The transmitted image shares are reconstructed using simple logical computation. In this paper, we propose a secure

This paper investigates the effect of both decoding and decompression on the Speaker Identification (SI) in a remote access system. The coding and compression processes are used for the communication purpose as a normal action taken for voice communication over Internet or mobile networks. In the proposed system, the speech signal is coded with the Linear Predictive Coding (LPC) technique. Also, the

Content Based Image Retrieval (CBIR) is a popular method to search and retrieve the similar images. For medical applications, it plays an important role to find the diseasessuch as breast cancer in human body. Many existing methods were presented for improving the performance of CBIR method. Nevertheless, retrieval time and accuracy of CBIR are further to be improved. To solve this issue, an optimal

This paper deals with bark texture representation at high scale-space levels for tree species identification. The proposed approach, named, a set of statistical radial binary patterns (sSRBP), is based on the combination of a novel scale-space sampling and an LBP-like radial encoding in the distribution level. This method aims at capturing and encoding large bark structure information. The multi-scale

ECG classification is important to the diagnosis of cardiovascular disease. This paper develops a robust and accurate algorithm for automatic detection of heart arrhythmias from ECG signals recorded with one lead. A novel model based on the convolutional neural network is proposed to extract low-level and high-level features of short term ECG. In addition, Information-Theoretic Metric Learning is utilized

American sign language recognition is still a research focus in computer vision community. Recently, most researches mainly extract low-level features for hand gesture recognition. These approaches perform poorly on recognizing gestures posed like a fist. In this paper, we propose a novel multimodal framework for sign language recognition system which exploits the Leap Motion Controller (LMC) and a

The present study reports classification and analysis of composite land features using fusion images obtained by fusing two original hyperspectral and multispectral datasets. The high spatial-spectral resolution, multi-instrument and multi-period satellite images were used for fusion. Three pixel level fusion based techniques, Color Normalized Spectral Sharpening (CNSS), Principal Component Spectral

Image/video processing in real-time is always in high demand for the quality of video. There are several factors which cause the loss of the video content, such as the type of transmission, missing data and especially data switch. Data switch generally occurs in the alternation of the video signal, which can cause the discontinuity of data during the video data stored in buffer or memory. The current

Background subtraction in traffic surveillance videos plays a crucial role in many high-level analytics and applications. Although great progress has been made in background subtraction, there are still many challenges in real traffic surveillance circumstances, such as camouflaged vehicles and dynamic background. This paper proposes a universal and accurate sampled-based vehicle detection method.

As the e-commerce shopping websites like Amazon become more and more popular, amounts of products spring up on the internet and bring great difficulties to product search. However, the conventional text-based search is confined to retrieving products relevant to query and personalized product search is still a challenging problem in e-commerce. Consequently, in this paper, we propose a personalized

Real-time sign language translation systems, that convert continuous sign sequences to text/speech, will facilitate communication between the deaf-mute community and the normal hearing majority. A translation system could be vision-based or sensor-based, depending on the type of input it receives. To date, most of the commercial systems for this purpose are sensor-based, which are expensive and not

Detecting small targets in large fields of view is a challenging task. Nowadays, many targets detection models based on the convolutional neural network (CNN) achieve excellent performance. However, these CNN-based detectors are inefficient when applied to tasks of real-time detection of small targets. This paper proposes a small-target detection model in large fields of view based on the tectofug

The main challenge for American Standard Code for Information Interchange (ASCII) based image encryption methods is to increase security with less computational cost. Earlier, well known image encryption techniques are not only deficient in performance but also lacked in embedding of confidential data in an image using ASCII based methods. Therefore, this study aims to contribute an ASCII based efficient

Due to the increasing shortage of fish in the seas, Vessel Monitoring Systems (VMS) play a very important role in fishing activity monitoring, control and surveillance. In this context, the detection of fishing activities in prohibited zones is a critical task. Although position, speed and other information are provided by the VMS system, detecting fishing activities using only this type of information

Image segmentation is a popular technique that is used for extracting information from images, which has also gained a lot of interest lately due to its importance in different scientific fields such as the medical field. This paper proposes a novel image segmentation technique using Expectation-Maximization (EM) clustering algorithm and Grasshopper Optimizer Algorithm (GOA). The proposed technique

Traditional camouflage pattern painting is not effective enough due to development of the high-tech reconnaissance. The recently proposed digital pattern painting, a new form of camouflage pattern painting, which has better performance in countering reconnaissance. In this study, we present a novel design and evaluation of digital camouflage pattern based on spot combination. Firstly, we compared three

How to measure the distance between heterogeneous data is still an open problem. Many research works have been developed to learn a common subspace where the similarity between different modalities can be calculated directly. However, most of existing works focus on learning a latent subspace but the semantically structural information is not well preserved. Thus, these approaches cannot get desired

Face alignment and cross-modal face transfer are two important tasks for automatic face analysis in computer vision. Over the years, they have been extensively studied. Recently, deep neural networks have attracted much research attention for both face alignment and face transfer. With the prevalence of the consumer depth sensor, depth-based face alignment and cross-modal (image and depth) are increasingly

This paper proposes Local Photometric Attributes (LPA) for the characterization of mammographic masses as benign or malignant. LPA measures the local information over the optical density image which suppresses the background region and provides more details about the mass lesion. The evaluation of the proposed approach is conducted by incorporating the mammograms of two benchmark databases—mini-MIAS